scholarly journals The use of satellite data for monitoring rivers in the Amu Darya basin

2020 ◽  
Vol 223 ◽  
pp. 03008
Author(s):  
Ildar Mukhamedjanov ◽  
Anna Konstantinova ◽  
Evgeniy Loupian
Keyword(s):  
Time Series ◽  
New Technology ◽  
Satellite Observation ◽  
Observation Time ◽  
Water Bodies ◽  
Satellite Monitoring ◽  
Amu Darya ◽  
Ground Station ◽  
State Of Water ◽  
Further Development

The paper explores the organization of satellite monitoring of water bodies in Central Asia on the example of the Amu Darya river in a specialized satellite monitoring system EcoSatMS (http://suvo.geosmis.ru). The potential and prospects of using the new technology of virtual gauging stations to control the state of water bodies, as well as restoring the values of daily runoff at a point remote from the ground station for some distance are highlighted. Evaluation of the effectiveness of the implementation of the virtual gauging stations technique in flow of automated calculations allows to take the research as a basis for further development of individual tools for analyzing satellite observation time series and the EcoSatMS in general.

New insights into magmatic processes from integrated satellite observation, trajectory analysis and magma ascent modelling

2021 ◽  
Author(s):  
Mike Burton ◽  
Giuseppe La Spina ◽  
Catherine Hayer ◽  
Benjamin Esse
Keyword(s):  
Time Series ◽  
Trajectory Analysis ◽  
High Spatial Resolution ◽  
Satellite Observation ◽  
Magma Ascent ◽  
Satellite Monitoring ◽  
Plume Height ◽  
So2 Flux ◽  
Magmatic Processes ◽  
Global Coverage

<p>Analysis of TROPOMI data with plume trajectory tools opens the possibility of new insights into volcanic / magmatic processes from two data sources: SO2 flux time series and plume height time series. In this paper we investigate results from explosive eruptions and attempt to explain the results with a magma ascent conduit model. The combination of plume height and gas flux data with a model of the magma ascent process provides a toolkit which allows us to constrain magma reservoir processes from satellite monitoring data. The combination of modelling and observations opens a new volcanological research frontier, because the TROPOMI sensor has daily global coverage, a high spatial resolution and is sensitive enough to detect many small-medium explosions globally, so that a large inventory of explosive activity can be characterised. </p>

Exploring the dynamic contribution behavior of editors in wikis based on time series analysis

2016 ◽  
Vol 50 (1) ◽  
pp. 41-57 ◽  
Author(s):  
Linghe Huang ◽  
Qinghua Zhu ◽  
Jia Tina Du ◽  
Baozhen Lee
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Time Series Data ◽  
Time Of Day ◽  
Observation Time ◽  
Series Data ◽  
Clustering Methods ◽  
Content Type ◽  
Free Rider Problem ◽  
Series Analysis

Purpose – Wiki is a new form of information production and organization, which has become one of the most important knowledge resources. In recent years, with the increase of users in wikis, “free rider problem” has been serious. In order to motivate editors to contribute more to a wiki system, it is important to fully understand their contribution behavior. The purpose of this paper is to explore the law of dynamic contribution behavior of editors in wikis. Design/methodology/approach – After developing a dynamic model of contribution behavior, the authors employed both the metrological and clustering methods to process the time series data. The experimental data were collected from Baidu Baike, a renowned Chinese wiki system similar to Wikipedia. Findings – There are four categories of editors: “testers,” “dropouts,” “delayers” and “stickers.” Testers, who contribute the least content and stop contributing rapidly after editing a few articles. After editing a large amount of content, dropouts stop contributing completely. Delayers are the editors who do not stop contributing during the observation time, but they may stop contributing in the near future. Stickers, who keep contributing and edit the most content, are the core editors. In addition, there are significant time-of-day and holiday effects on the number of editors’ contributions. Originality/value – By using the method of time series analysis, some new characteristics of editors and editor types were found. Compared with the former studies, this research also had a larger sample. Therefore, the results are more scientific and representative and can help managers to better optimize the wiki systems and formulate incentive strategies for editors.

scholarly journals Systematic Water Fraction Estimation for a Global and Daily Surface Water Time-Series

2021 ◽  
Vol 13 (14) ◽  
pp. 2675
Author(s):  
Stefan Mayr ◽  
Igor Klein ◽  
Martin Rutzinger ◽  
Claudia Kuenzer
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Spatial Resolution ◽  
Pure Water ◽  
Feature Space ◽  
Observation Time ◽  
Temporal Information ◽  
Landsat 8 ◽  
Water Fraction ◽  
Classification Probability

Fresh water is a vital natural resource. Earth observation time-series are well suited to monitor corresponding surface dynamics. The DLR-DFD Global WaterPack (GWP) provides daily information on globally distributed inland surface water based on MODIS (Moderate Resolution Imaging Spectroradiometer) images at 250 m spatial resolution. Operating on this spatiotemporal level comes with the drawback of moderate spatial resolution; only coarse pixel-based surface water quantification is possible. To enhance the quantitative capabilities of this dataset, we systematically access subpixel information on fractional water coverage. For this, a linear mixture model is employed, using classification probability and pure pixel reference information. Classification probability is derived from relative datapoint (pixel) locations in feature space. Pure water and non-water reference pixels are located by combining spatial and temporal information inherent to the time-series. Subsequently, the model is evaluated for different input sets to determine the optimal configuration for global processing and pixel coverage types. The performance of resulting water fraction estimates is evaluated on the pixel level in 32 regions of interest across the globe, by comparison to higher resolution reference data (Sentinel-2, Landsat 8). Results show that water fraction information is able to improve the product’s performance regarding mixed water/non-water pixels by an average of 11.6% (RMSE). With a Nash-Sutcliffe efficiency of 0.61, the model shows good overall performance. The approach enables the systematic provision of water fraction estimates on a global and daily scale, using only the reflectance and temporal information contained in the input time-series.

scholarly journals Estimation of Infiltration Volumes and Rates in Seasonally Water-Filled Topographic Depressions Based on Remote-Sensing Time Series

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7403
Author(s):  
Pavel P Fil ◽  
Alla Yu Yurova ◽  
Alexey Dobrokhotov ◽  
Daniil Kozlov
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Shallow Groundwater ◽  
Remote Sensing Data ◽  
Water Bodies ◽  
Water Infiltration ◽  
Temporary Ponds ◽  
Small Water ◽  
Negative Exponential ◽  
Topographic Depressions

In semi-arid ecoregions of temperate zones, focused snowmelt water infiltration in topographic depressions is a key, but imperfectly understood, groundwater recharge mechanism. Routine monitoring is precluded by the abundance of depressions. We have used remote-sensing data to construct mass balances and estimate volumes of temporary ponds in the Tambov area of Russia. First, small water bodies were automatically recognized in each of a time series of high-resolution Planet Labs images taken in April and May 2021 by object-oriented supervised classification. A training set of water pixels defined in one of the latest images using a small unmanned aerial vehicle enabled high-confidence predictions of water pixels in the earlier images (Cohen’s Κ = 0.99). A digital elevation model was used to estimate the ponds’ water volumes, which decreased with time following a negative exponential equation. The power of the exponent did not systematically depend on the pond size. With adjustment for estimates of daily Penman evaporation, function-based interpolation of the water bodies’ areas and volumes allowed calculation of daily infiltration into the depression beds. The infiltration was maximal (5–40 mm/day) at onset of spring and decreased with time during the study period. Use of the spatially variable infiltration rates improved steady-state shallow groundwater simulations.

scholarly journals Water vapor pressure trends in south and southwest Iran

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 335-348
Author(s):  
YOUNES KHOSRAVI ◽  
HASAN LASHKARI ◽  
HOSEIN ASAKEREH
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Vapor Pressure ◽  
Water Vapor Pressure ◽  
Sen’S Slope Estimator ◽  
Sen’S Slope ◽  
Ground Station ◽  
Mk Test ◽  
Slope Estimator ◽  
The Persian Gulf

Recognitionanddetectionofclimaticparameters inhave animportant role inclimate change monitoring. In this study, the analysis of oneofthe most importantparameters, water vapor pressure (WVP), was investigated. For this purpose, two non-parametric techniques, Mann-Kendall and Sen's Slope Estimator, were used to analyze the WVP trend and to determine the magnitude of the trends, respectively. To analyze these tests, ground station observations [10 stations for period of 44 years (1967-2010)] and gridded data [pixels with the dimension of 9 × 9 km over a 30-year period (1981-2010)] in South and SouthwestofIran were used. By programming in MATLAB software, the monthly, seasonal and annual WVP time series were extracted and MK and Sen's slope estimator tests were done. The results of monthly MK test on ground station observations showed that the significant downward trends are more considerable than significant upward trends. It also showed that the WVP highest frequency was more in warm months, April to September and the highest frequency of significant trends slope was in February and May. The spatial distribution of MK test of monthly gridded WVP time series showed that the upward trends were detected mostly in western zone and near the Persian Gulf in August. On the other hand, the downward trends through months. The maximum and minimum values of positive trends slope occurred in warm months and cold months, respectively. The analysis of the MK test of the annual WVP time series indicated the upward significant trends in the southeast and southwest zones of study area.  

Temporal and spatial considerations in data-model comparisons involving transient paleoclimatic simulations

2021 ◽  
Author(s):  
Patrick Bartlein ◽  
Sandy Harrison
Keyword(s):  
Time Series ◽  
Best Practices ◽  
Data Model ◽  
Environmental Data ◽  
Climatic Effects ◽  
Data Archiving ◽  
Model Comparisons ◽  
Climate Reconstructions ◽  
Temporal And Spatial ◽  
Further Development

<p>The increasing availability of time-evolving or transient palaeoclimatic simulations makes it imperative to develop “best-practices” for comparing simulations with palaeoclimatic observations including both climate reconstructions and environmental data.  There are two sets of considerations, temporal and spatial, that should guide those comparisons.  The chronology of simulations can in some ways be viewed as exact, as determined by the insolation forcing, but data archiving and reporting conventions, such as reporting summaries that use the modern calendar (that leads to the long-recognized palaeo-calendar effect) can, if ignored, lead to “built-in” temporal offsets of thousands of years in such features as temperature or precipitation maxima or minima.  Likewise, there are age uncertainties in time series of palaeoclimatic data that are often ignored, despite the fact that these are large during “climatically interesting times” such as the Younger Dryas chronozone.  Similarly, although model resolution is increasing, there is still a mismatch in topography (and its climatic effects) between a model and the “real world” sensed by the palaeoclimatic data sources. </p><p>There are existing approaches for dealing with some of these issues, such as calendar-adjustment programs, Monte-Carlo approaches for describing age uncertainties in palaeoclimate time series, or clustering approaches for objectively defining appropriate regions for the calculation of area averages, but there is certainly room for further development.  This abstract is intended to serve as platform for discussion of some of best practices for data-model comparisons in transient mode.</p>

A linear/non-linear hybrid time-series model to investigate the depletion of inland water bodies

2020 ◽  
Author(s):  
Babak Zolghadr-Asli ◽  
Maedeh Enayati ◽  
Hamid Reza Pourghasemi ◽  
Mojtaba Naghdyzadegan Jahromi ◽  
John P. Tiefenbacher
Keyword(s):  
Time Series ◽  
Time Series Model ◽  
Water Bodies ◽  
Inland Water ◽  
Non Linear ◽  
Inland Water Bodies
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